Abstract
Traditionally within the mining industry, single models for both grade and geology of orebodies are created upon which all mine development decisions are based. These models provide a single interpretation of the extent and continuity of the mineralization envelope based on solids and sections interpreted from relatively widely spaced drilling. The inherent variable behavior of grade and geology cannot be understood from a single estimated resource model. To account for uncertainty in the geology and mineralization envelope, Newmont Mining Corporation uses multiple-point statistics (MPS), an emerging spatial simulation framework, which can be employed to generate multiple, geologically realistic, realizations of data representing attributes of mineral deposits that display complex non-linear features. MPS uses a conceptual model of the geology, termed a training image, to infer these high-order spatial relationships. A detailed application of the MPS algorithm at the structurally controlled Apensu gold deposit, Ghana, demonstrates the practical intricacies of the MPS framework and documents efficiency and effectiveness. Multiple realizations of the Apensu deposit allow for an assessment of the geologic and volumetric uncertainty, which is further combined with grade simulations to generate a more complete picture of the true uncertainty of the deposit.
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Acknowledgements
This paper details ongoing investigations into the application of conditional simulation for risk analysis and would not have been possible without the dedication to innovation by managers and directors at Newmont Mining Corporation. The help of Afia F. Baah, Mining Engineer at Apensu is gratefully acknowledged.
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Jones, P., Douglas, I. & Jewbali, A. Modeling Combined Geological and Grade Uncertainty: Application of Multiple-Point Simulation at the Apensu Gold Deposit, Ghana. Math Geosci 45, 949–965 (2013). https://doi.org/10.1007/s11004-013-9500-3
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DOI: https://doi.org/10.1007/s11004-013-9500-3